Ninghao Liu

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Xia "Ben" HuAssociate Professor of Computer Science, Rice UniversityEmail yang diverifikasi di rice.edu
Mengnan DuAssistant Professor, New Jersey Institute of TechnologyEmail yang diverifikasi di njit.edu
Fan YangAssistant Professor of Computer Science, Wake Forest UniversityEmail yang diverifikasi di wfu.edu
Tianming LiuDistinguished Research Professor of Computer Science, University of GeorgiaEmail yang diverifikasi di cs.uga.edu
Qiaoyu (Smach) TanAssistant Professor of Computer Science, New York University (Shanghai)Email yang diverifikasi di nyu.edu
Xuansheng WuUniversity of GeorgiaEmail yang diverifikasi di uga.edu
Yucheng ShiUniversity of GeorgiaEmail yang diverifikasi di uga.edu
Xiang LiAssistant Professor, Massachusetts General Hospital and Harvard Medical SchoolEmail yang diverifikasi di mgh.harvard.edu
Xiao HuangAssistant Professor at The Hong Kong Polytechnic UniversityEmail yang diverifikasi di comp.polyu.edu.hk
Jundong LiAssistant Professor, University of VirginiaEmail yang diverifikasi di virginia.edu
Rui ChenChief Scientist, Samsung Ads / Senior Director of Engineering (AI), Samsung Research AmericaEmail yang diverifikasi di samsung.com
Hongxia YangProfessor, HK Polytechnic UniversityEmail yang diverifikasi di polyu.edu.hk
Xiaoming ZhaiAssociate Professor, University of GeorgiaEmail yang diverifikasi di uga.edu
Xiaotian (Max) HanCase Western Reserve UniversityEmail yang diverifikasi di case.edu
Qingquan SongLinkedInEmail yang diverifikasi di linkedin.com
James CaverleeProfessor, Computer Science and Engineering, Texas A&M UniversityEmail yang diverifikasi di cse.tamu.edu

Ikuti

Ninghao Liu

Assistant Professor, University of Georgia

Email yang diverifikasi di uga.edu - Beranda

Explainable AI Fairness in Machine Learning Graph Mining Anomaly Detection


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Techniques for interpretable machine learning M Du, N Liu, X Hu Communications of the ACM 63 (1), 68-77, 2019	1542	2019
Explainability for large language models: A survey H Zhao, H Chen, F Yang, N Liu, H Deng, H Cai, S Wang, D Yin, M Du ACM Transactions on Intelligent Systems and Technology 15 (2), 1-38, 2024	478	2024
Auggpt: Leveraging chatgpt for text data augmentation H Dai, Z Liu, W Liao, X Huang, Y Cao, Z Wu, L Zhao, S Xu, F Zeng, W Liu, ... IEEE Transactions on Big Data, 2023	376*	2023
G-mixup: Graph data augmentation for graph classification X Han, Z Jiang, N Liu, X Hu International Conference on Machine Learning, 8230-8248, 2022	237	2022
An embarrassingly simple approach for trojan attack in deep neural networks R Tang, M Du, N Liu, F Yang, X Hu Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020	219	2020
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper) G Mai, W Huang, J Sun, S Song, D Mishra, N Liu, S Gao, T Liu, G Cong, ... ACM Transactions on Spatial Algorithms and Systems, 2024	187*	2024
Towards explanation of dnn-based prediction with guided feature inversion M Du, N Liu, Q Song, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	164	2018
Sparse-interest network for sequential recommendation Q Tan, J Zhang, J Yao, N Liu, J Zhou, H Yang, X Hu Proceedings of the 14th ACM international conference on web search and data …, 2021	158	2021
S2GAE: self-supervised graph autoencoders are generalizable learners with graph masking Q Tan, N Liu, X Huang, SH Choi, L Li, R Chen, X Hu Proceedings of the sixteenth ACM international conference on web search and …, 2023	148*	2023
Edits: Modeling and mitigating data bias for graph neural networks Y Dong, N Liu, B Jalaian, J Li Proceedings of the ACM web conference 2022, 1259-1269, 2022	145	2022
Deep representation learning for social network analysis Q Tan, N Liu, X Hu Frontiers in big Data 2, 2, 2019	143	2019
In-processing modeling techniques for machine learning fairness: A survey M Wan, D Zha, N Liu, N Zou ACM Transactions on Knowledge Discovery from Data 17 (3), 1-27, 2023	141	2023
Artificial general intelligence (AGI) for education E Latif, G Mai, M Nyaaba, X Wu, N Liu, G Lu, S Li, T Liu, X Zhai arXiv preprint arXiv:2304.12479, 2023	111	2023
Learning to hash with graph neural networks for recommender systems Q Tan, N Liu, X Zhao, H Yang, J Zhou, X Hu Proceedings of The Web Conference 2020, 1988-1998, 2020	110	2020
Contextual outlier interpretation N Liu, D Shin, X Hu Proceedings of the 27th International Joint Conference on Artificial …, 2018	104	2018
Is a single vector enough? exploring node polysemy for network embedding N Liu, Q Tan, Y Li, H Yang, J Zhou, X Hu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019	102	2019
Applying large language models and chain-of-thought for automatic scoring GG Lee, E Latif, X Wu, N Liu, X Zhai Computers and Education: Artificial Intelligence 6, 100213, 2024	88	2024
Adversarial detection with model interpretation N Liu, H Yang, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	82	2018
Dynamic memory based attention network for sequential recommendation Q Tan, J Zhang, N Liu, X Huang, H Yang, J Zhou, X Hu Proceedings of the AAAI conference on artificial intelligence 35 (5), 4384-4392, 2021	76	2021
Accelerated Local Anomaly Detection via Resolving Attributed Networks. N Liu, X Huang, X Hu IJCAI, 2337-2343, 2017	74	2017

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